Legal AI for mid-market companies
Run contracts like an enterprise without enterprise overhead
Ask Genie to draft a customer agreement for our mid-market workflow...
Ask Genie to draft a customer agreement for our mid-market workflow...
Ask Genie to review this counterparty MSA against our mid-market playbook...
Ask Genie to find the right template for our mid-market workflow...
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Contract velocity for the scale-up stage
GenieAI is the AI legal assistant trusted by 200,000+ business teams. We draft, review, and negotiate every contract a scaling business signs - customer, vendor, employment, partnership - with current-law accuracy across 150+ jurisdictions.
- Auto-draft customer, vendor, and employment agreements at scale
- Standardise playbook across functions before legal becomes the bottleneck
- 500+ scale-up-ready templates across 150+ jurisdictions, free to use
What you can do
Use cases for Mid-Market
Each of these is a workflow Genie handles end-to-end. Click any use case to see how it works.
How we compare
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Common questions
Mid-Market FAQs
Legal has become the bottleneck as we grow. What is the fix?
Usually not more headcount. Most of the queue is the same incoming terms being reviewed repeatedly, so settling those positions once as a playbook and reviewing against it removes the wait without giving up control.
The risk of a bottleneck is not delay on its own. It is that commercial teams start signing without review because waiting costs them the deal.
How do we set contract standards the commercial team will actually follow?
Write them as positions rather than policy: what we accept, what we can concede, and what has to escalate. Anything outside the agreed positions is flagged rather than silently approved.
Standards fail when they live in a document nobody opens. They work when they are applied to the contract in front of the person doing the deal.
What contract risks do scaling businesses miss most often?
Uncapped liability and broad indemnities on customer paper, auto-renewal and price escalation in supplier terms, missing data processing agreements, and IP assignments that were never signed by contractors.
Each looks minor in isolation, which is why they are missed. They matter at diligence, where they are repriced rather than negotiated.
How do we move from ad hoc contracts to a repeatable process?
Start with the documents you sign most often, agree the standard positions for them, and put those into a playbook. Master service agreements, NDAs and supplier agreements usually account for most of the volume.
Working in that order matters. Standardising the long tail first produces a lot of documentation and very little reduction in risk.
Do we need a contract management system as well?
Not necessarily at this stage. Storage and reporting help once the volume is large, but for most scaling businesses the exposure is in what the contracts say rather than in finding them again afterwards.
It is worth being clear which problem you are solving. Consistent drafting and review addresses risk; a repository addresses retrieval.
Is GenieAI right for a mid-market legal team?
Yes. GenieAI scales from teams of 2 to teams of 200 with the same product - pricing scales linearly, no enterprise tier required for core features.
How fast can a mid-market team onboard?
Most mid-market teams are productive within a week. Playbook ingestion, integration setup, and team training are bundled into onboarding - no professional-services engagement required.
What ROI do mid-market customers see?
Mid-market customers typically report 60-80% reduction in contract review cycle time, with proportional reductions in external-counsel spend. Most reach payback within 3-6 months.
Trusted by 200,000+ users
Drafts, reviews, and negotiates contracts autonomously.
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